Neural-Network-Based Controller Used for Directional Control of Tunneling Machine
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概要
- 論文の詳細を見る
This paper presents a method for implementing neural control systems to control mechanical systems. The neural control systems are designed focusing on the difference in the neural network learning speed between an adaptive and a learning scheme, so the control systems are constructed with both an adaptive neural identifier and a learning neural controller. To ensure both robustness and stability at the beginning of learning, the neural control systems incorporate a conventional feedback controller. The use of neural control systems to control a tunneling machine, used to construct underground conduits for telecommunication cables, is numerically simulated to investigate the proposed controller's capability and characteristics. A simple model of the tunneling machine, which is used as the controlled plant, is derived by analyzing the force acting on the tunneling machine from the surrounding ground. Simulation results confirm the feasibility of the neural control systems and show that the direction of the tunneling machine can be controlled by using the NN learning ability.
- 一般社団法人日本機械学会の論文
- 1996-12-15
著者
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Hosaka H
Univ. Tokyo Tokyo Jpn
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Takahashi Kazuhiko
Integrated Information & Energy Systems Laboratories, Nippon Telegraph and Telephone Corporation
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Hosaka Hiroshi
Integrated Information & Energy Systems Laboratories, Nippon Telegraph and Telephone Corporation
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Takahashi Kazuhiko
Integrated Information & Energy Systems Laboratories Nippon Telegraph And Telephone Corporation
関連論文
- Neural-Network-Based Controller Used for Directional Control of Tunneling Machine
- Neural-Network-Based Controller with Application to a Flexible Micro-Actuator : Direct Neural Controller and its Extension to an Open-Loop Neural Controller (Special Issue on Micromachine Technology)
- Application of an Immune Feedback Mechanism to Control Systems
- A Radial-Basis-Function-Network-Based Controller Derived from a Neural-Network-Based Controller and its Application to Controlling Mechanical Systems